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Bioinformatics 2009 25(12):i137-i144; doi:10.1093/bioinformatics/btp213
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Predicting functionality of protein–DNA interactions by integrating diverse evidence

Duygu Ucar 1,2, Andreas Beyer 3, Srinivasan Parthasarathy 1 and Christopher T. Workman 2,*

1Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA, 2Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby Denmark and 3Biotechnology Center, TU Dresden, 01062 Dresden, Germany

*To whom correspondence should be addressed.


  Abstract

Chromatin immunoprecipitation (ChIP-chip) experiments enable capturing physical interactions between regulatory proteins and DNA in vivo. However, measurement of chromatin binding alone is not sufficient to detect regulatory interactions. A detected binding event may not be biologically relevant, or a known regulatory interaction might not be observed under the growth conditions tested so far. To correctly identify physical interactions between transcription factors (TFs) and genes and to determine their regulatory implications under various experimental conditions, we integrated ChIP-chip data with motif binding sites, nucleosome occupancy and mRNA expression datasets within a probabilistic framework. This framework was specifically tailored for the identification of functional and non-functional DNA binding events. Using this, we estimate that only 50% of condition-specific protein–DNA binding in budding yeast is functional. We further investigated the molecular factors determining the functionality of protein–DNA interactions under diverse growth conditions. Our analysis suggests that the functionality of binding is highly condition-specific and highly dependent on the presence of specific cofactors. Hence, the joint analysis of both, functional and non-functional DNA binding, may lend important new insights into transcriptional regulation.

Contact: workman{at}cbs.dtu.dk


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